People are increasingly interacting with computing devices and relying on these devices for information, recommendations, and other services to assist them in their day-to-day tasks. But understanding the user's spoken words and intent by the computing device in these interactions remains a difficult technical problem. In such interactions, users are often left frustrated by the inability of their computerized personal assistant applications or services to understand them, their intent, or anticipate their needs.
At the same time, many users of computing devices have repeating patterns of usage. For example, a user may launch an email app on their mobile device every workday morning, before starting work, browse to a favorite news website over lunchtime, call a close friend or family member on their drive home from work, or use their laptop computer to plan their annual summer vacation around May. By learning these patterns of user activity, the computerized personal-assistant applications and services can provide improved user experiences including improved understanding of the user's speech and the user's intent.